class_docstr: Tokenizes a tensor of UTF-8 strings.
  
  SentencePiece is an unsupervised text tokenizer and detokenizer. It is used
  mainly for Neural Network-based text generation systems where the vocabulary
  size is predetermined prior to the neural model training. SentencePiece
  implements subword units with the extension of direct training from raw
  sentences.
  
  Before using the tokenizer, you will need to train a vocabulary and build a
  model configuration for it. Please visit the [Sentencepiece
  repository](https://github.com/google/sentencepiece#train-sentencepiece-model)
  for the most up-to-date instructions on this process.
docstr: Returns the vocabulary size.
  
    The number of tokens from within the Sentencepiece vocabulary provided at
    the time of initialization.
  
  Args:
    name: The name argument that is passed to the op function.
  
  Returns:
    A scalar representing the vocabulary size.
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code: def vocab_size(self, name=None):
      """Returns the vocabulary size.
  
        The number of tokens from within the Sentencepiece vocabulary provided at
        the time of initialization.
  
      Args:
        name: The name argument that is passed to the op function.
  
      Returns:
        A scalar representing the vocabulary size.
      """
      with ops.name_scope(
          name, "SentencepieceTokenizerVocabSize", [self]
      ):
          return (
              gen_sentencepiece_tokenizer.sentencepiece_vocab_size_op(
                  self._model_resource.resource_handle
              )
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensorflow.python.eager import monitoring
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops.ragged import ragged_conversion_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged.ragged_tensor import RaggedTensor
  from tensorflow.python.trackable import resource
  from tensorflow_text.python.ops.tokenization import Detokenizer
  from tensorflow_text.python.ops.tokenization import TokenizerWithOffsets
  from tensorflow.python.framework import load_library
  from tensorflow.python.platform import resource_loader
label_desc: Use image node_id 5 for calling the SentencepieceTokenizer obj's underlying member method code with example usage: obj.vocab_size(name) and returns: gen_sentencepiece_tokenizer